Summary
In this chapter, you have seen an introduction to neural networks and how they can be used in practice using popular frameworks like TensorFlow and PyTorch. You have seen how to translate those concepts into the graph domain, and you have learned the basics of three modern frameworks for deep learning on graphs: PyG, StellarGraph, and DGL. It is worth noting that some concepts may seem unclear at this point. Don’t worry! In the next chapters, all these concepts will be examined in more detail.
Get ready to embark on our journey into the GraphML landscape as we explore Unsupervised Graph Learning in the next chapter!